Randomization tests allow simple and unambiguous tests of null hypotheses, by comparing observed data to a null ensemble in which experimentally-controlled variables are randomly resampled. In behavioral and neuroscience experiments, however, the stimuli presented often depend on the subject's previous actions, so simple randomization tests are not possible. We describe how conditional randomization can be used to perform exact hypothesis tests in this situation, and illustrate it with two examples. We contrast conditional randomization with a related approach of tangent randomization, in which stimuli are resampled based only on events occurring in the past, which is not valid for all choices of test statistic. We discuss how to design experiments that allow conditional randomization tests to be used.

翻译：随机化检验通过将观测数据与随机重采样实验控制变量的零假设集合进行比较，可提供简单且明确的零假设检验。然而在行为科学和神经科学实验中，由于呈现的刺激往往取决于受试者先前的行为反应，因此无法直接应用简单的随机化检验。本文阐述了如何利用条件随机化在此类情境中执行精确假设检验，并通过两个案例进行说明。我们将条件随机化与基于时间回溯重采样刺激的切线随机化方法进行对比，指出后者并非对所有检验统计量都有效。最后讨论如何设计实验以支持条件随机化检验的应用。